Document production environments, such as print shops, convert printing orders, such as print jobs, into finished printed material. A print shop may process print jobs using resources such as printers, cutters, collators and other similar equipment. Typically, resources in print shops are organized such that when a print job arrives from a customer at a particular print shop, the print job can be processed by performing one or more production functions.
Scheduling architectures that organize print jobs arriving at a document production environment and route the print jobs to autonomous cells are known in the art and are described in, for example, U.S. Pat. No. 7,051,328 to Rai et al. and U.S. Pat. No. 7,065,567 to Squires et al., the disclosures of which are incorporated by reference in their entirety. Methods for automatically distributing jobs to a receiver on a network using devices are known in the art and are described in, for example, U.S. Pat. No. 5,513,126 to Harkins et al., the disclosure of which is incorporated by reference in its entirety.
It is common for print shops to receive print jobs having variable job sizes. Problems arise when a wide distribution of document or print job sizes exists. This may be referred to as a heavy-tailed distribution. Heavy-tailed distributions usually require significant data before the mean distribution can be computed with accuracy. For normal distributions, the sample mean converges to the population mean inversely as the square root of the sample size. For heavy-tailed distributions, however, the sample mean converges to the population mean inversely as n1-(1/α). As such, as α approaches 1, the convergence rate may be very poor and the estimates of averages from simulations done on heavy-tailed distributions may be inaccurate.
Transaction print environments that process jobs having a heavy-tailed job-size distribution tend to have inefficient job flows. This is because these environments typically handle very large and very small jobs that are all part of one job pool. It is likely that several small jobs may be delayed if they are queued behind a very large job. Similarly, large jobs can experience flow interruptions if several small jobs requiring multiple setups are ahead of the large jobs in the queue.
Systems and methods for effectively processing heavy-tailed distributions in document production environments, notwithstanding poor convergence rates and possible inaccurate estimates of averages, would be desirable.